2 citations · 3 across the 3 of their papers we have counts for
7 papers
Efficient mixture model for clustering of sparse high dimensional binary data
Marek Śmieja, Krzysztof Hajto, Jacek Tabor
In this paper we propose a mixture model, SparseMix, for clustering of sparse high dimensional binary data, which connects model-based with centroid-based clustering. Every group i…
Spherical Wards clustering and generalized Voronoi diagrams
Marek Śmieja, Jacek Tabor
Gaussian mixture model is very useful in many practical problems. Nevertheless, it cannot be directly generalized to non Euclidean spaces. To overcome this problem we present a sph…
Semi-supervised model-based clustering with controlled clusters leakage
Marek Śmieja, Łukasz Struski, Jacek Tabor
In this paper, we focus on finding clusters in partially categorized data sets. We propose a semi-supervised version of Gaussian mixture model, called C3L, which retrieves natural…
Pointed subspace approach to incomplete data
Łukasz Struski, Marek Śmieja, Jacek Tabor
Incomplete data are often represented as vectors with filled missing attributes joined with flag vectors indicating missing components. In this paper we generalize this approach an…
ICA based on the data asymmetry
Przemysław Spurek, Jacek Tabor, Przemysław Rola +1
Independent Component Analysis (ICA) - one of the basic tools in data analysis - aims to find a coordinate system in which the components of the data are independent. Most of exist…
Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation
Wojciech Marian Czarnecki, Rafał Józefowicz, Jacek Tabor
Representation learning is currently a very hot topic in modern machine learning, mostly due to the great success of the deep learning methods. In particular low-dimensional repres…